Supercapacitors ageing prediction by neural networks

Abstract

Supercapacitors are devices used in wide range of applications, for example in automotive applications. Therefore, it is important to monitor and track their ageing. This paper presents a new approach for predicting the ageing of supercapacitors based on the neo-fuzzy neuron in association with the one-step ahead time series prediction. Ageing information collected from the measurement of the equivalent series resistance and the double layer capacitance are used to train the neo-fuzzy neuron. The obtained model is used as a prognostic tool in order to forecast the ageing of supercapacitors. The performance of the proposed approach is evaluated by using an experimental platform for ageing supercapacitors. The experimental results show that the neo-fuzzy prediction model can track the ageing of supercapacitors.